An agent-based tool for micro-level simulation of transport chains (TAPAS) is described. It is more powerful than traditional approaches as it is able to capture the interactions between individual actors of a transport chain, as well as their heterogeneity and decision making processes. Whereas traditional approaches rely on assumed statistical correlation between different parameters, TAPAS relies on causality, i.e., the decisions and negotiations that lead to the transports being performed. An additional advantage is that TAPAS is able to capture time aspects, such as, the influence of timetables, arrival times, and time-differentiated taxes and fees. TAPAS is composed of two layers, one layer simulating the physical activities taking place in the transport chain, e.g., production, storage, and transports of goods, and another layer simulating the different actors' decision making processes and interaction. The decision layer is implemented as a multi-agent system using the JA...
Paul Davidsson, Johan Holmgren, Jan A. Persson, Li